Tag SNP selection for prediction of adaptation traits in Braford and Hereford cattle using Bayesian methods.

REIMANN, F. A.; CAMPOS, G. S.; JUNQUEIRA, V. S.; COMIN, H. B.; SOLLERO, B. P.; CARDOSO, L. L.; COSTA, R. F. da; BOLIGON, A. A.; YOKOO, M. J. I.; CARDOSO, F. F.

Tag SNP selection for prediction of adaptation traits in Braford and Hereford cattle using Bayesian methods.

Autores

Descripción

This study utilized Bayesian inference in a genome-wide association study (GWAS) to identify genetic markers associated with traits relevant to the adap- tation of Hereford and Braford cattle breeds. We focused on eye pigmentation (EP), weaning hair coat (WHC), yearling hair coat (YHC), and breeding stand- ard (BS). Our dataset comprised 126,290 animals in the pedigree. Out of these, 233 sires were genotyped using high-density (HD) chips, and 3750 animals with medium-density (50 K) single-nucleotide polymorphism (SNP) chips. Employing the Bayes B method with a prior probability of π = 0.99, we identified and tagged single nucleotide polymorphisms (Tag SNPs), ranging from 18 to 117 SNPs de- pending on the trait. These Tag SNPs facilitated the construction of reduced SNP panels. We then evaluated the predictive accuracy of these panels in compari- son to traditional medium-density SNP chips. The accuracy of genomic predic- tions using these reduced panels varied significantly depending on the clustering method, ranging from 0.13 to 0.65. Additionally, we conducted functional enrich- ment analysis that found genes associated with the most informative SNP mark- ers in the current study, thereby providing biological insights into the genomic basis of these traits.